Duke University anticipates $100,000 or more per year in energy savings, while increasing processing power.

Nicole Hemsoth

Duke University anticipates $100,000 or more per year in energy savings, while increasing processing power.

Crunching large quantities of data is a crucial component of modern academic life. On university campuses, everyone from chemists and engineers to researchers in sociology, economics and even literature needs access to high-performance computing (HPC). At Duke University, the Duke Shared Cluster Resource (DSCR) supports these needs for professors across the spectrum.

The DSCR serves 650 end users in 70 different research groups. One major research area that the DSCR caters to is the bioinformatics community. “Several of our professors are doing genome comparisons,” says John Pormann, Duke’s director of scalable computing. “Some researchers are building models that establish probabilities for when certain genes arose—and when species with a common ancestor became distinct. One is trying to develop the tree of life for a set of fungi by looking at genetics.”

Many bioinformatics researchers need to process an unprecedented volume of data. “One of our professors is working with a grant agency that gives grant recipients the newest, fastest gene-sequencing machine, rather than offering a large amount of money,” Pormann says. “Professors receive a cutting-edge gene sequencer, which spits out enormous amounts of data. They depend on the DSCR to provide an HPC environment that supports their data analysis needs.”

Cutting-edge research using limited power

In its efforts to meet those needs, the DSCR faces substantial logistical challenges. The building that houses the data center was constructed to hold classrooms, not a server farm. The data center has already maxed out the amount of electricity that can run through the building’s conduit. Its floor is raised only 12 inches, and the last air conditioning installation involved overhead units because the installers weren’t convinced they could push enough air through the floor to keep all the equipment cool.

“If we exceed the capacity of our current air conditioning unit, we have to go back to the drawing board,” says Pormann. “Adding power to our current location would be expensive because we’d have to bring in new power lines from the street, digging up sidewalks and parking lots in the process. Moving to a new data center would cost well into the six figures. We’d like to stay where we are, but that means we need to use the power and cooling in that room as efficiently as possible. It’s imperative as we expand our computing power that we keep our power and cooling resources constant.”

168 fewer watts per server

The DSCR needs to maximize the ratio of processing power to energy consumption for servers in its HPC cluster. The cluster encompasses 729 servers, from Dell PowerEdge M610 blade servers with Intel Xeon processor 5600 series to seven-year-old rack-mounted boxes. Oracle Grid Engine dynamically provisions application workloads to the most appropriate resources in the cluster.

To gain insight into the DSCR’s balance between processing power and consumption of energy and cooling resources, Pormann embarked on research of his own. He studied how CPU utilization correlates to power consumption in the cluster. For more than a year he collected data on the wattage drawn by the cluster’s primary servers, all Dell dual-CPU, quad-core machines, running their normal workload.

“Across the board, from idle performance up to 100 percent CPU utilization, we see significant drops in power consumption on new Dell blade servers,” Pormann reports. “The form factor itself reduces energy needs because blades have fewer, larger, more efficient power supplies, and that’s clearly a factor in the sharp decline in power consumption that we see between the PowerEdge 1950 servers and the PowerEdge M610 blades.”

Comparing the Dell PowerEdge M600 blades with Intel Xeon processor E5420 and the PowerEdge M610 blades with Intel Xeon processor E5520 shows the difference a more efficient processor can make. “The across-the-board drop of roughly 20 watts is primarily attributable to CPU improvements,” says Pormann. “This suggests that all workloads would see significant improvements in energy savings from simply moving to the new CPUs. No matter what load is placed on the system, we should see significant reductions in power usage.”

$100,000-plus per year in energy cost savings

In addition to helping the DSCR stay in its current location, reducing servers’ power usage—both directly and by reducing air conditioning usage—saves the university money on an ongoing basis. “Even with North Carolina’s below-average power costs, we’re seeing savings of $100,000 or more per year, just by reducing our energy usage,” Pormann says.

As energy consumption falls, processing power grows dramatically with each new generation of Dell blades. “Every time we add a Dell PowerEdge M610 blade, we can pull older nodes from the cluster and retain the same processing power,” Pormann says. “When we buy new equipment, our users are always astounded at how much faster their jobs run. But we can’t directly calculate how many older nodes are comparable to a new blade. For one researcher, a new blade might replace eight older servers, but for another researcher that ratio might be 12 to 1.”

The DSCR just implemented six new 12-CPU-core PowerEdge M610 blades with Intel Xeon processor 5600 series and 96 gigabytes of memory per blade. “We’re really looking forward to seeing what they can do,” says Pormann. “Our early data indicates that they use no more power than our 8-CPU-core PowerEdge M610 blades with Intel Xeon processor E5520. So we should see a 50 percent increase in computational capability with zero increase in power consumption.”

Available capacity in the HPC cluster indicates that the new Dell PowerEdge blades are giving the cluster a substantial boost in processing power. Historically, the DSCR has run at about 70 percent of its total capacity. Since recent additions of Dell blades, utilization has declined to around 50 percent, so the cluster’s unused capacity has increased by as much as 30 percent. “Because we have more head room, we have the capability for researchers to do different kinds of experimentation,” says Pormann. “They don’t have to worry about wasting capacity anymore. They appreciate that whenever they need more computational power, it’s here.”

Pormann attributes the performance gains of the latest Dell servers to advancements, in part, in their management of memory. “More and more of our users are asking about large memory configurations,” he says. “It seems research projects are starting to be constrained by node memory performance and capacity. Over the last nine months, three different professors involved in bioinformatics have asked me whether they can get 256 or 512 gigabytes of memory in a single blade. One of them is working with images, each of which is on the order of a terabyte in size. I told them that systems with those memory configurations are on the Dell road map. The integrated memory controller and the Intel QuickPath architecture give the Dell blades exceptional bandwidth for memory processing.”

The DSCR further improves performance within the cluster using the Intel Compiler Suite. “We’re leveraging the Intel compilers as much as possible,” Pormann says. “What we’ve seen so far is that the Intel compilers, compared with the open source compilers, provide anywhere from 20 to 50 percent improvement in performance. You run the exact same C code through the Intel compiler, and the executable is faster. The Intel compilers seem to take advantage of all the bells and whistles in these new Intel processors.”

Server management tools bring additional efficiencies

Now Pormann is figuring out better ways to use the tools at his disposal to manage power for the cluster’s servers. The DSCR uses Dell Chassis Management Controller (CMC) to monitor energy consumption of the blades. Then IPMItool, an open source utility, exports this data to the Oracle Grid Engine. “Dell has its own add-ons to IPMItool,” Pormann says. “We were able to talk to the Dell engineering group, and they gave us information about the command line interfaces we could use to gather this data for Grid Engine.”

Pormann and his team currently can use Dell CMC to remotely control power usage within the cluster. “Dell CMC should enable us to easily power off machines and idle groups of machines to reduce the cluster’s overall heat load,” says Pormann.

The next step is to automate the process of powering off servers through Oracle Grid Engine. “An idle machine still uses more than 100 watts,” says Pormann. “Throttling the CPU may reduce power consumption, but it should be used in conjunction with powering off unused machines. And our systems should be capable of powering machines down automatically so someone doesn’t have to push buttons 24×7. Knowing we have this potential in the blades helps us justify our continuing commitment to building out these tools.”

Mapping the cluster’s future

Duke purchases most of the cluster’s hardware from Dell for several reasons. One is the product road map from Dell and Intel. “We like Dell’s track record of always putting the newest equipment from Intel in their hardware,” Pormann says. “When Intel announces a new chip, we know we’re going to see it in Dell’s equipment shortly. Knowing what’s coming on those road maps enables us to spend our money very wisely.”

Perhaps the most important reason why the DSCR continues to purchase from Dell is that Pormann has always been pleased with the support he’s received. “Anytime we have a hardware issue, Dell cross-ships us parts and gives us access to engineers,” says Pormann. “As long as Dell and Intel continue to work on efficiency in the ratio of processing power to energy consumption, we’ll be able to continue to increase computational power, even as we stay in our current data center.”

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